Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Communications of the ACM
Information Retrieval
MovieLens unplugged: experiences with an occasionally connected recommender system
Proceedings of the 8th international conference on Intelligent user interfaces
User profiling with Case-Based Reasoning and Bayesian Networks
International Joint Conference, 7th Ibero-American Conference, 15th Brazilian Symposium on AI, IBERAMIA-SBIA 2000, Open Discussion Track Proceedings on AI
Dependency networks for inference, collaborative filtering, and data visualization
The Journal of Machine Learning Research
Clustering Approach for Hybrid Recommender System
WI '03 Proceedings of the 2003 IEEE/WIC International Conference on Web Intelligence
Evaluating collaborative filtering recommender systems
ACM Transactions on Information Systems (TOIS)
Collaborative filtering based on iterative principal component analysis
Expert Systems with Applications: An International Journal
Collaborative filtering using interval estimation naïve Bayes
AWIC'03 Proceedings of the 1st international Atlantic web intelligence conference on Advances in web intelligence
Collaborative filtering with the simple Bayesian classifier
PRICAI'00 Proceedings of the 6th Pacific Rim international conference on Artificial intelligence
Empirical analysis of predictive algorithms for collaborative filtering
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Aggregating preference graphs for collaborative rating prediction
Proceedings of the fourth ACM conference on Recommender systems
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This paper presents a model designed under the formalism of Bayesian Networks to deal with the problem of collaborative recommendation. It has been designed to perform efficient and effective recommendations. We also consider the fact that the user can usually use vague ratings for the products, which might be represented as fuzzy labels. The complete proposal is evaluated with MovieLens.